diff --git a/python/paddle_serving_client/__init__.py b/python/paddle_serving_client/__init__.py
index d524201e45b0b948cbd3738fedb878e5f9b53e02..bea80f84bc9d29cabe4f31af612c694980b71d09 100644
--- a/python/paddle_serving_client/__init__.py
+++ b/python/paddle_serving_client/__init__.py
@@ -74,7 +74,7 @@ class Client(object):
         self.fetch_names_ = []
         self.client_handle_ = None
         self.result_handle_ = None
-        self.feed_shapes_ = []
+        self.feed_shapes_ = {}
         self.feed_types_ = {}
         self.feed_names_to_idx_ = {}
         self.rpath()
@@ -106,13 +106,23 @@ class Client(object):
             0]] + ["--tryfromenv=" + ",".join(read_env_flags)])
         self.feed_names_ = [var.alias_name for var in model_conf.feed_var]
         self.fetch_names_ = [var.alias_name for var in model_conf.fetch_var]
-        self.feed_shapes_ = [var.shape for var in model_conf.feed_var]
         self.feed_names_to_idx_ = {}
         self.fetch_names_to_type_ = {}
         self.fetch_names_to_idx_ = {}
+        self.lod_tensor_set = set()
+        self.feed_tensor_len = {}
         for i, var in enumerate(model_conf.feed_var):
             self.feed_names_to_idx_[var.alias_name] = i
             self.feed_types_[var.alias_name] = var.feed_type
+            self.feed_shapes_[var.alias_name] = var.shape
+
+            if var.is_lod_tensor:
+                self.lod_tensor_set.add(var.alias_name)
+            else:
+                counter = 1
+                for dim in self.feed_shapes_[var.alias_name]:
+                    counter *= dim
+                self.feed_tensor_len[var.alias_name] = counter
 
         for i, var in enumerate(model_conf.fetch_var):
             self.fetch_names_to_idx_[var.alias_name] = i
@@ -137,6 +147,14 @@ class Client(object):
     def get_fetch_names(self):
         return self.fetch_names_
 
+    def shape_check(self, feed, key):
+        seq_shape = 1
+        if key in self.lod_tensor_set:
+            return
+        if len(feed[key]) != self.feed_tensor_len[key]:
+            raise SystemExit("The shape of feed tensor {} not match.".format(
+                key))
+
     def predict(self, feed={}, fetch=[]):
         int_slot = []
         float_slot = []
@@ -145,6 +163,7 @@ class Client(object):
         fetch_names = []
 
         for key in feed:
+            self.shape_check(feed, key)
             if key not in self.feed_names_:
                 continue
             if self.feed_types_[key] == int_type: